| Literature DB >> 27541949 |
Weixiong Jiang1,2,3,4, Feng Shi3, Jian Liao1, Huasheng Liu1, Tao Wang3,5, Celina Shen3, Hui Shen4, Dewen Hu4, Wei Wang6, Dinggang Shen7,8.
Abstract
Studies on antisocial personality disorder (ASPD) subjects focus on brain functional alterations in relation to antisocial behaviors. Neuroimaging research has identified a number of focal brain regions with abnormal structures or functions in ASPD. However, little is known about the connections among brain regions in terms of inter-regional whole-brain networks in ASPD patients, as well as possible alterations of brain functional topological organization. In this study, we employ resting-state functional magnetic resonance imaging (R-fMRI) to examine functional connectome of 32 ASPD patients and 35 normal controls by using a variety of network properties, including small-worldness, modularity, and connectivity. The small-world analysis reveals that ASPD patients have increased path length and decreased network efficiency, which implies a reduced ability of global integration of whole-brain functions. Modularity analysis suggests ASPD patients have decreased overall modularity, merged network modules, and reduced intra- and inter-module connectivities related to frontal regions. Also, network-based statistics show that an internal sub-network, composed of 16 nodes and 16 edges, is significantly affected in ASPD patients, where brain regions are mostly located in the fronto-parietal control network. These results suggest that ASPD is associated with both reduced brain integration and segregation in topological organization of functional brain networks, particularly in the fronto-parietal control network. These disruptions may contribute to disturbances in behavior and cognition in patients with ASPD. Our findings may provide insights into a deeper understanding of functional brain networks of ASPD.Entities:
Keywords: Antisocial personality disorder; Brain connectome; Functional connectivity; Modularity; Topological organization
Mesh:
Year: 2017 PMID: 27541949 PMCID: PMC5362344 DOI: 10.1007/s11682-016-9572-z
Source DB: PubMed Journal: Brain Imaging Behav ISSN: 1931-7557 Impact factor: 3.978